from torch import nn

from .base_ga_model import BaseGA9Ind, GA_Type


class GA_Linear(BaseGA9Ind):
    def __init__(self, before_dim, after_dim, *args):
        super(GA_Linear, self).__init__(GA_type=GA_Type.Linear, *args)
        self.before_dim = before_dim
        self.after_dim = after_dim
        self.conv = nn.Conv2d(in_channels=before_dim, out_channels=after_dim, kernel_size=3, stride=1, padding=1)

    def real_forward(self, x, *args):
        return self.conv(x)
